Estimating random walk centrality in networks

dc.contributor.authorJohnson, B.
dc.contributor.authorKirkland, S.
dc.date.accessioned2019-05-06T21:57:24Z
dc.date.available2019-05-06T21:57:24Z
dc.date.issued2019
dc.date.submitted2019-05-06T01:24:53Zen
dc.description.abstractRandom walk centrality (equivalently, the accessibility index) for the states of a time-homogeneous irreducible Markov chain on a finite state space is considered. It is known that the accessibility index for a particular state can be written in terms of the first and second moments of the first return time to that state. Based on that observation, the problem of estimating the random walk centrality of a state is approached by taking realizations of the Markov chain, and then statistically estimating the first two moments of the corresponding first return time. In addition to the estimate of the random walk centrality, this method also yields the standard error, the bias and a confidence interval for that estimate. For the case that the directed graph of the transition matrix for the Markov chain has a cut-point, an alternate strategy for computing the random walk centrality is outlined that may be of use when the centrality values are of interest for only some of the states. In order to illustrate the effectiveness of the results, estimates of the random walk centrality arising from random walks for several directed and undirected graphs are discussed.en_US
dc.identifier.doihttps://doi.org/10.1016/j.csda.2019.04.009
dc.identifier.urihttp://hdl.handle.net/1993/33887
dc.language.isoengen_US
dc.publisherComputational Statistics & Data Analysis 138, pp. 190-200.en_US
dc.rightsopen accessen_US
dc.subjectRandom walk centralityen_US
dc.subjectNetwork centralityen_US
dc.subjectAccessibility indexen_US
dc.subjectMarkov chainsen_US
dc.subjectMean first passage timesen_US
dc.subjectBootstrapen_US
dc.titleEstimating random walk centrality in networksen_US
dc.typeArticleen_US
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